Marta Yebra

Orcid: 0000-0002-4049-9315

According to our database1, Marta Yebra authored at least 30 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Examining the Transferability of Remote-Sensing-Based Models of Live Fuel Moisture Content for Predicting Wildfire Characteristics.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024

A Survey on IoT Ground Sensing Systems for Early Wildfire Detection: Technologies, Challenges, and Opportunities.
IEEE Access, 2024

2023
Improving wildfire occurrence modelling by integrating time-series features of weather and fuel moisture content.
Environ. Model. Softw., December, 2023

IoT Ground Sensing Systems for Early Wildfire Detection: Technologies, Challenges and Opportunities.
CoRR, 2023

2022
RADAR-Vegetation Structural Perpendicular Index (R-VSPI) for the Quantification of Wildfire Impact and Post-Fire Vegetation Recovery.
Remote. Sens., 2022

Multi-modal temporal CNNs for live fuel moisture content estimation.
Environ. Model. Softw., 2022

2021
Relationships between Burn Severity and Environmental Drivers in the Temperate Coniferous Forest of Northern China.
Remote. Sens., 2021

Modelling wildfire occurrence at regional scale from land use/cover and climate change scenarios.
Environ. Model. Softw., 2021

Global trends in vegetation seasonality in the GIMMS NDVI3g and their robustness.
Int. J. Appl. Earth Obs. Geoinformation, 2021

Global fuel moisture content mapping from MODIS.
Int. J. Appl. Earth Obs. Geoinformation, 2021

2020
Remote Sensing of Burn Severity Using Coupled Radiative Transfer Model: A Case Study on Chinese Qinyuan Pine Fires.
Remote. Sens., 2020

Correction: Wang, L., et al. Assessment of the Dual Polarimetric Sentinel-1A Data for Forest Fuel Moisture Content Estimation. Remote Sensing 2019, 11(13), 1568.
Remote. Sens., 2020

Investigating Live Fuel Moisture Content Estimation in Fire-Prone Shrubland from Remote Sensing Using Empirical Modelling and RTM Simulations.
Remote. Sens., 2020

A Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models.
Remote. Sens., 2020

Assessment of generalized allometric models for aboveground biomass estimation: A case study in Australia.
Comput. Electron. Agric., 2020

2019
Assessment of the Dual Polarimetric Sentinel-1A Data for Forest Fuel Moisture Content Estimation.
Remote. Sens., 2019

A multiscale morphological algorithm for improvements to canopy height models.
Comput. Geosci., 2019

A hybrid method for segmenting individual trees from airborne lidar data.
Comput. Electron. Agric., 2019

Burn Severity Estimation in Northern Australia Tropical Savannas Using Radiative Transfer Model and Sentinel-2 Data.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Evaluating the Sentinel-2a Satellite Data for Fuel Moisture Content Retrieval.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

Estimation of Forest Structure with the Vegetation Structure Perpendicular Index (VSPI) for Dynamic Fire Spread Simulations.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019

2018
Near Real-Time Extracting Wildfire Spread Rate from Himawari-8 Satellite Data.
Remote. Sens., 2018

Mapping Live Fuel Moisture Content and Flammability for Continental Australia Using Optical Remote Sensing.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

Retrieval of Fuel Moisture Content from Himawari-8 Product: Towards Real-Time Wildfire Risk Assessment.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

The Vegetation Structure Perpendicular Index for Wildfire Severity and Forest Recovery Monitoring.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018

2017
Retrieval of forest fuel moisture content using a coupled radiative transfer model.
Environ. Model. Softw., 2017

Development of a predictive model for estimating forest surface fuel load in Australian eucalypt forests with LiDAR data.
Environ. Model. Softw., 2017

A radiative transfer model-based method for the estimation of grassland aboveground biomass.
Int. J. Appl. Earth Obs. Geoinformation, 2017

2016
Deriving comprehensive forest structure information from mobile laser scanning observations using automated point cloud classification.
Environ. Model. Softw., 2016

2009
Generation of a Species-Specific Look-Up Table for Fuel Moisture Content Assessment.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2009


  Loading...